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A Feasibility Study for the Automated Monitoring and Control of Mine Water Discharges
2017 WV Mine Drainage Taskforce Chris Vass Aaron Noble, PhD Mining Engineering West Virginia University Morgantown, WV April 11, 2017
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Presentation Outline 1 2
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BACKGROUND BENCH-SCALE SYSTEM
PROOF-OF-CONCEPT RESULTS
ONGOING WORK & CONCLUSIONS
MAMDANI CONTROLLER
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MOTIVATION Automated Outlet Treatment
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Challenges in CAPP
Remote Locations No Utilities Area/Access Limited by Topography Several parameter limits: pH TSS, Fe, Al, Mn, etc. Lab Results Take Time
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Traditional Practices in CAPP Rob
Can get to the remote locations, but takes time.
May make it to problematic sites once or twice per day.
Not available 24/7/365.
Not an environmental chemist, but knows practical water treatment.
Will eventually retire or find another job.
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Research Objectives Problem Statements:
Given the unique environmental challenges in CAPP, traditional methods of water monitoring and treatment are costly and inefficient.
The current and future regulatory trajectory may deem many of these practices cost prohibitive.
Research Objectives:
Evaluate the technical and economic feasibility of automated monitoring and advanced control algorithms for chemical treatment of mine water discharges
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Generic Controller
Generic pH Control Diagram
AMD Treatment System
Process Set Point (pH = 7)
Outlet pH
Process Disturbances: -Incoming pH -Flow Rate -Atmospheric Conditions
Current System Conditions
Treatment Flow Rate
Control
Algorithm
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0 250 500 750 1000 1250
Stea
dy S
tate
pH
Base Treatment Flowrate (ml/min)
Titration of HCl with Na2CO3
Problem: pH Treatment is Nonlinear!
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BENCH-SCALE SYSTEM CONSTRUCTION
Automated Outlet Treatment
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Components
Reactor
Conductivity Sensor
pH Sensor
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Components
Transmitters/Power Supply DAQ Unit
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Components
Supply Pump Treatment Pump
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Components
Baffle Installed Baffle
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Bench Scale Model
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MAMDANI FUZZY CONTROLLER Automated Outlet Treatment
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Advanced Control Techniques
MF1 MF2 MF3 MF4
ANN’s Fuzzy Logic ANFIS
Several advanced pH control techniques exist; however, they are currently unproven in a mine environmental setting.
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Modeling Approach
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Fuzzy Logic - Basics
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Fuzzy Logic – Membership Functions
Use of non-precise classes to segment process behavior
Error
MF1 MF2 MF3 MF4
MF1 MF2 MF3 MF4
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Membership Functions
Doesn’t neglect “Rob’s” intuition, 30+ years of AMD research, or the real-time data…
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0 250 500 750 1000 1250
pH
Base Treatment Flowrate (cc/min)
High pH
Low pH
Neutral pH
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RESULTS & DISCUSSION Automated Outlet Treatment
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pH Control – Experimental Tests
Test No. Simulated Condition 1 Normal field Operations under steady state conditions
2 Unsteady flow rate
3 Changing pH set point
4 Large surge in flow rate that interrupts flow recording device
5 Change in feed water pH
6 Removal of pond baffle
7 Multiple disturbances/perturbations
Define acceptable range as ±0.5 pH point.
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pH Control – Steady State
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pH Control – Varying Flow Rates & Set Point
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pH Control – Change in Feed pH
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ONGOING WORK & CONCLUSIONS
Automated Outlet Treatment
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Ongoing Work Implementation of control scheme at AMD treatment site
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Summary & Conclusions Environmental monitoring and treatment costs can be significant
and require perpetual attention. Laboratory tests have shown that fuzzy logic is a feasible control
option. The controller used in this testing was able to withstand multiple
perturbations and maintain pH within ±0.5.
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Questions? For more information, please contact: Chris Vass
Acknowledgements:
